Reading #3: “Those Look Similar!” Issues in Automating Gesture Design Advice (Long)

Summary

In this paper, the author describes their gesture design tool named quill. This system performs user initiated and automatic analysis on different gesture classes to determine which ones may be recognized as similar by either the computer system or a human. The quill system uses the algorithm developed by Rubine to classify gesture classes based on ten to fifteen examples for each gesture class.The paper also discusses various challenges that arise when designing a system to give feedback to designers of gestures. The issues of timing of analysis and feedback, how much feedback, and what kind of feedback should be given are all discussed. The paper finishes by discussing some shortcomings of recognizing human-perceived similarities and how these can be improved in the future.

Discussion

This paper discusses some important issues for any developer creating a system that is meant to provide feedback to its users. The timing and presentation of the feedback given in quill is provided in a way as to minimize disrupting a gesture designer during the creative process. Providing feedback about the machine similarity of gesture classes can be valuable to a new gesture designer who is unfamiliar with the feature set provided by Rubine and the way in which a computer classifies gestures. 

Reading #2 Specifying Gestures by Example (Rubine)

Summary
This paper first describes some features of a gesture based drawing program which uses GRANDMA (Gesture Recognizers Automated in a Novel Direct Manipulation) developed by Dean Rubine. The system uses training examples of various gestures to recognizer and classify the input from the user. Several training examples of the "delete" gesture are shown to illustrate the variety possible in a single gesture. Next the features used for gesture recognition are described. These features are used in combination with a linear classifier to determine which class a gesture belongs to. A few example gesture sets are also given along with their respective recognition rates to demonstrate the high accuracy provided by GRANDMA.

Discussion
In 1991, Rubine's GRANDMA system provided a solid framework for gesture recognition based on example gestures. This method proved relatively simple compared to implementing the hand-coded recognizers available at the time. Having a system that can be trained using example gestures allows for easier custom implementations in various types of programs. The feature set chosen by Rubine combined with the linear classifier is sufficient to repeatedly distinguish most common gestures as well as numbers and letters as shown in Figure 9 of the paper.

Reading #1 Gesture Recognition (Hammond)

Summary
This article provides a good introduction to the field of gesture recognition and details how it differs from sketch recognition in that a gesture must be drawn in the same manner every time in order to be recognized. An explanation of the 13 features developed by Dean Rubine for gesture recognition is then given. These features form the core of many gesture recognition systems used today such as Christopher Long's Quill system which is explained next. Long's system adds 11 features but disregards the 2 features dealing with time from Rubine's original system. Wobbrock's $1 gesture recognizer is then explained to show a different method of gesture recognition. Instead of relying on features, Wobbrock's method computes distances between sample points to determine which class a gesture belongs to.

Discussion
This reading introduces the reader to a few of the fundamental gesture recognition techniques. For someone who is new to the field, it provides insight into how gesture recognition can be accomplished and gives a feel for what features of a gesture are important when attempting recognition. This is done by exploring some of the very important papers in the field of gesture recognition.

Some General Info

1. Photo of yourself.

See profile pic.
2. E-mail address (e.g., yourname at domain.com).

jag427 at gmail dot com

3. Graduate standing (e.g., 3rd year Phd) (e.g., 3rd Year PhD, 2nd Year Masters, 1st Year PhD w/ Masters).

2nd Year M.E.

4. Why are you taking this class?

Curiosity about the field. 

5. What experience do you bring to this class?

Not much but plan to leave with plenty.

6. What do you expect to be doing in 10 years?

Working in industry or running a business, preferably the latter

7. What do you think will be the next biggest technological advancement in computer science?

Quantum computing. I don't know much about it but it should be interesting.

8. What was your favorite course when you were an undergraduate (computer science or otherwise)?

Embedded Systems courses

9. What is your favorite movie and why?

Gladiator. It has nothing to do with CS but I could watch that movie all day

10. If you could travel back in time, who would you like to meet and why?

Leonardo da Vinci. I'd give him all my books and course work then see what kind of future I come back to. 

11, Give some interesting fact about yourself.

I've never been out of country but I really want to explore the rest of this world.